Cai, B., Dunson, D. B., & Stanford, J. B. (2010). Dynamic model for multivariate markers of fecundability. Biometrics, 66(3), 905-913. https://doi.org/10.1111/j.1541-0420.2009.01327.x
Cai B, Dunson DB, Stanford JB. Dynamic model for multivariate markers of fecundability. Biometrics. 2010;66(3):905-913. doi:10.1111/j.1541-0420.2009.01327.x
Cai, B., et al. "Dynamic model for multivariate markers of fecundability." Biometrics, vol. 66, no. 3, 2010, pp. 905-913.
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National Institute of Environmental Health Sciences00j4k1h63
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Abstract
Dynamic latent class models provide a flexible framework for studying biologic processes that evolve over time. Motivated by studies of markers of the fertile days of the menstrual cycle, we propose a discrete-time dynamic latent class framework, allowing change points to depend on time, fixed predictors, and random effects. Observed data consist of multivariate categorical indicators, which change dynamically in a flexible manner according to latent class status. Given the flexibility of the framework, which incorporates semi-parametric components using mixtures of betas, identifiability constraints are needed to define the latent classes. Such constraints are most appropriately based on the known biology of the process. The Bayesian method is developed particularly for analyzing mucus symptom data from a study of women using natural family planning.
Minjeur M et al., 2026·Journal of Restorative Reproductive Medicine·Free to read
Infertility is a clinical condition that is recognized by the symptom of an inability to conceive through sexual intercourse or to sustain a pregnancy, with that symptom indicating underlying male and/or female pathology.
This definition of infertility was developed through a structured, consensus-informed process involving broad stakeholder engagement. Initially, multiple definitions currently used by various medical professional organizations were reviewed, and a definition document was drafted and submitted to the Board of Directors of the International Institute for Restorative Reproductive Medicine (IIRRM). All IIRRM members were invited to provide feedback on the draft. Approximately 2,500 individuals and 44 organizations from 92 countries were then invited to review the proposed document, representing clinical, scientific, patient, policy, and advocacy perspectives. Submitted comments were reviewed thematically, with suggested revisions evaluated for clarity, clinical relevance, inclusiveness, and consistency with contemporary restorative reproductive medicine. Following this review, 3 substantive changes, 18 minor changes, and 15 citation corrections were incorporated into the final draft which resulted in a revised definition intended to better reflect the medical, social, and practical realities of modern infertility evaluation and care. Final approval by the IIRRM Board of Directors was unanimous.
Kahn LG et al., 2026·JAMA Network Open·Free full text on PubMed Central
Increasing numbers of children are conceived using infertility treatment; concerns remain about potential effects on child neurodevelopment. To evaluate whether infertility treatment is associated with child neurodevelopment and whether such an association may be attributable to underlying subfecundity. DESIGN, SETTING, This cohort study was conducted among mother-child dyads in the National Institutes of Health Environmental Influences on Child Health Outcomes (ECHO) Cohort, with infants conceived between 1998 and 2022. Associations of subfecundity and infertility treatment with neurodevelopmental outcomes were assessed among children ages 2 to 10 years. Data were analyzed from May 14, 2025, to March 31, 2026. Subfecundity was defined as prior consultation for, treatment of, or diagnosis of infertility for either partner; at least 2 prior miscarriages; or ever having had unprotected heterosexual intercourse for 12 months without conceiving. Infertility treatment was categorized as in vitro fertilization (IVF) or non-IVF treatment. Harmonized caregiver responses to the Strengths and Difficulties Questionnaire and the Child Behavior Checklist yielded continuous raw scores for externalizing and internalizing problems. The total raw Social Responsiveness Scale (SRS) score quantified autism-like symptoms. Caregivers reported physician diagnosis of autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). Among 15 382 mother-infant dyads, there were 14 191 unique maternal participants (mean [SD] age at delivery, 30.9 [5.33] years; 8780 parous participants [57.1%]). ASD and ADHD were diagnosed in 876 offspring (7.6%) and 819 offspring (7.1%), respectively. In generalized linear models, subfecundity was associated with higher externalizing problem and SRS scores among all pregnancies (externalizing problems: b = 0.47 [95% CI, 0.14-0.81]; SRS score: b = 1.08 [95% CI, 0.01-2.14]) and when restricted to natural conceptions (externalizing problems: b = 0.45 [95% CI, 0.07-0.83]; SRS score: b = 1.12 [95% CI, -0.09 to 2.34]). Offspring of parents with subfecundity had higher odds of ASD (overall: odds ratio [OR], 1.27 [95% CI, 1.03-1.57]; natural conceptions: OR, 1.31 [95% CI, 1.04-1.64]). Children conceived via non-IVF treatment had higher odds of ADHD compared with those conceived via natural conception with subfecundity (OR, 1.77 [95% CI, 1.16-2.68]) or without subfecundity (OR, 1.54 [95% CI, 1.05-2.25]). There were no significant associations for IVF treatment. In this large US cohort study, subfecundity was associated with elevated scores for caregiver-reported symptoms of behavioral problems and higher odds of ASD diagnosis, independent of infertility treatment. Non-IVF treatment was associated with ADHD, warranting further research into specific indications for treatment that may increase risk of offspring neurodevelopmental problems.
Stanford JB et al., 2026·Frontiers in Reproductive Health·Free full text on PubMed Central
Background The total fertility rate (TFR) in most developed countries has been declining for decades. In the United States (U.S.), the total fertility rate has remained below replacement level since 2007. Subfertility affects at least 15% of women or couples over their reproductive lifespan and contributes to reduced TFR. Restorative reproductive medicine (RRM) is a medically based approach to subfertility care that can be delivered in primary care settings to increase live birth rates. Objective To estimate the theoretical impact of use of RRM among subfertile couples in the United States. Methods We conducted a simulation study. Model inputs included the number of women of reproductive age in the United States by 5-year age groups; current age-specific and total fertility rates; the proportion of women in each age group with subfertility; estimated spontaneous live birth rates among women with subfertility; and age-specific crude live birth rates with RRM treatment. We evaluated fifteen scenarios including sensitivity analyses: two different varying assumptions for spontaneous conception (25% vs. 50%), two levels of RRM utilization among subfertile women (20% vs. 50%), three different estimates of the number of subfertile women who would be potentially eligible for RRM treatment, and 4 different levels of effectiveness (live birth) from RRM treatment. Results The baseline TFR in the United States was 1.77 during 2015-2019, and 13.5% of women ages 20-44 were estimated to have subfertility. In a conservative scenario (50% spontaneous births; 20% RRM utilization; married women trying to conceive for at least 12 months, 20.7% RRM live births), the TFR increased to 1.79, representing a 1.0% relative increase (absolute +0.02). In an optimistic scenario (25% spontaneous births; 50% RRM utilization; all subfertile women), the TFR increased to 2.02, a 14.5% relative increase (absolute +0.26), approaching replacement-level fertility. Conclusion Simulation results suggest that expanding access to RRM within primary care settings could meaningfully increase the U.S. TFR, by reducing unresolved subfertility. Realizing this potential would require policy and health system changes to address workforce capacity, insurance coverage, and equitable access. These findings underscore the potential contribution of non-IVF fertility care pathways in addressing population-level fertility decline.
This multicenter study has produced a database of 7017 menstrual cycles contributed by 881 women. It provides improved knowledge on length and location of the "fertile window" (identified as of up to 12 days duration) and the patterns and level of daily conception probability. The day of ovulation was identified in each cycle from records of basal body temperature and mucus symptoms. By referencing days of intercourse to the surrogate ovulation markers, estimates of daily fecundability were computed either directly or by the Scwartz model, both for single and multiple acts of intercourse in the fertile window. The relationship between coital pattern and fecundability has been explored. Univariate analysis underlines the significant link with fecundability only of the woman's reproductive history.
With the collaboration of Italian centres providing services on natural family planning, a prospective study collected data on 2755 menstrual cycles of 193 women. A database was constructed using information on the daily characteristics of cervical mucus and episodes of intercourse. Taking the day of peak mucus as a conventional marker of ovulation, the database identified the length (12 days) and location of a 'window' of potential fertility, the highest level of conception probability being confined to the central five to six days. Univariate analysis provided evidence of the impact on fecundability of the woman's age and the basic infertile pattern of a cycle. Several analytical approaches highlighted the relationship between daily mucus characteristics and levels of fecundability
The percentage of 869 women in five countries capable of being taught to recognize the periovulatory cervical mucus symptom of the fertile period was determined in a prospective multicentre trial of the ovulation method of natural family planning. The women were ovulating, of proven fertility, represented a spectrum of cultures and socioeconomic levels, and ranged from illiteracy to having postgraduate education. In the first of three standard teaching cycles, 93% recorded on interpretable ovulatory mucus pattern. Eighty-eight per cent of subjects successfully completed the teaching phase; 7% discontinued for reasons other than pregnancy, including 1.3% who failed to learn the method. Forty-five subjects (5%) became pregnant during the average 3.1-cycle teaching phase. The average number of days of abstinence required by the rules of the method was 17 in the third teaching cycle (58.2% of the average cycle length). To what extent the findings of this study can be extended to other couples remains to be demonstrated.
The only way to be sure of avoiding pregnancy is for a couple to abstain from sexual intimacy during the fertile phase of the woman's cycle. Billings showed by reference to hormonal parameters that after competent instruction in the ovulation method women can identify the fertile phase of their cycle. If abstinence during the fertile phase is replaced by coitus combined with barrier methods, the pregnancy rate will be higher. The hormonal monitoring has revealed that the Peak Symptom as defined in the ovulation method is the most accurate biological marker of the time of ovulation. The cervical mucus pattern reflects the estrogen levels during follicular ripening from its commencement, and the Peak Symptom reflects a sharp cut-off effected by the elevation of the progesterone level at the time of ovulation. This means that once the mucus begins to be observed as a warning of the approach of ovulation, the woman needs to follow the changing characteristics on a daily basis in order to be certain that she recognizes ovulation.
B Cai, Joe Stanford, Joey Stanford, J Stanford, Dave Dunson, D Dunson
PMID 19751248 19751248 DOI 10.1111/j.1541-0420.2009.01327.x 10.1111/j.1541-0420.2009.01327.x Cai et al. 2009, Cai 2009
Cite this article
Cai, B., Dunson, D. B., & Stanford, J. B. (2010). Dynamic model for multivariate markers of fecundability. Biometrics, 66(3), 905-913. https://doi.org/10.1111/j.1541-0420.2009.01327.x
Cai B, Dunson DB, Stanford JB. Dynamic model for multivariate markers of fecundability. Biometrics. 2010;66(3):905-913. doi:10.1111/j.1541-0420.2009.01327.x
Cai, B., et al. "Dynamic model for multivariate markers of fecundability." Biometrics, vol. 66, no. 3, 2010, pp. 905-913.
Keywords
Bayes Theorem, Biomarkers, Female, Fertility, Humans, Male, Menstrual Cycle, Models, Statistical, Mucus, Natural Family Planning Methods, Time Factors, Biomarkers